1.[1 17]service quality assessment in insurance sector a comparative study between indian and chinese customers

Research Journal of Finance and Accounting www.iiste.org
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Service Quality Assessment in Insurance Sector: A Comparative
Study between Indian and Chinese Customers
Ravi Kant Sharma (Corresponding author)
Raj Kumar Goel Engineering College, Ghaziabad
Uttar Pradesh, India
ravikantgzb@gmail.com
M.R.Bansal
Institute of Business Management
B.R.Ambedkar University, Agra
Abstract
Globalisation and open market system have created the complex competitive environment not
only for the manufacturing sector but also for the service sector. Recent developments in
global economy have led the service companies especially the insurance companies to plan
and execute their strategies towards increasing customer satisfaction and loyalty through
improved service quality. The present study focuses on developing a valid and reliable
instrument to measure customer perceived service quality and comparing these between
Indian and Chinese Insurance companies. The resulting validated instrument comprised of six
dimensions: assurance, personalized financial planning, competence, corporate image,
tangibles and technology. The study finds that although both the countries are operating in
similar service environment but the responses to these service quality components differ from
customers of one country to another.
Keywords: Service Quality, Cross Cultural, Insurance, GAP analysis,
1. Introduction:
In recent years, there has been a resurgence of interest in services due to their ever-increasing
importance in both developed and developing countries (Hubner, 1997; Hunerberg and Mann,
1997; Keegan and Schlegelmilch, 2001; Muhlbacher et al., 1999). Over the past decades, the
share of GDP attributable to services has continued to grow in many countries and accounts
for more than 60 percent of the world output today (Kotabe and Helsen, 2004). This trend is
bound to continue in the future.
Services also represent a major driving force of international trade. Over the past years, the
share of services in total cross-border exports has risen constantly. As a consequence, service
marketers are dealing with an increasingly globalized environment, confronting new
opportunities for profit while facing world-class competitors. Liberalization and
internationalization has impacted in the way as service quality across the sectors has now
become an important means of differentiation and path to achieve business success. Such
differentiation based on service quality can be a key source of competitiveness for insurance
companies and hence have implication for leadership in such organizations. The trend of
insurance companies shifting from a product-focused view to a customer-focused one has
been developing recently as insurance products become increasingly hard to differentiate in
fiercely competitive markets. It is becoming desirable for insurance companies to develop a
customer centric approach for future survival and growth. The awareness has already dawned
that prompt, efficient and speedy service alone will tempt the existing customers to continue
and induce new customers to try the services of the company. In Asia there are two large

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economies which are grown in past one decade after implementing economic reforms this
study focuses on these two major economies of the Asia i.e. India and China.
China’s insurance industry is one of the fastest growing insurance industries across the globe.
While most of the countries worldwide are still witnessing brisk growth amid recovery,
Chinese insurance industry has already started growing by leaps and bounds, ending 2010
with a growth of around 33%. Life insurance products including health and personal
accidents resulted in maximum growth, accounting for a lion’s share of total insurance
premium written in the country. The Chinese insurance industry is expected to grow at a
CAGR of over 24% during 2011-2014.General insurance premium are also growing at a
rapid pace with burgeoning demand in various sub-segments. The report attempts to assess
market potential in each of the sub segments namely motor (auto), property, agriculture,
liability, cargo, and short-term personal accident insurance. Motor insurance accounts for a
major share of general insurance premium and is a key driver for future. The market will also
witness new and innovative insurance products in future to further increase penetration of the
industry in the country.
However, the insurance market in China still remains largely untapped. With insurance
penetration (in terms of GDP) at mere 3.4% at the end of 2009, China stands far behind than
the global average penetration of over 7%. Thus, the future of industry looks certainly
promising with ever strengthening distribution network, development of new channels for
sales, and positive indicators for foreign players. (Table1)
India was ranked 9th among 156 countries in the life insurance business as per data published
by Swiss Re. During the year 2009, life insurance premiums in India grew by 10.1 per cent
(inflation adjusted), while the global life insurance industry contracted by 2 per cent. The
share of Indian life insurance sector in the global market was 2.45 per cent during 2009, as
against 1.98 per cent in 2008.Since opening up of the Insurance sector in 1999, 40 private
companies have been granted license by 30th
September 2010 to conduct business in Life
Insurance and General Insurance. Of the 40, 22 are in the Life Insurance and 18 in General
Insurance. After the opening up of the sector, the average annual growth of first year’s
premium in the Life segment worked out of 47.06% and in the Non-Life segment it was
16.87%.
Today, hardly 20 per cent of the population in India is insured and insurance premium (life as
well as non-life) account for just 2 per cent of the GDP as against the G-7 average of 9.2 per
cent. A burgeoning middle class, high per capita savings and low penetration of insurance are
some of the key factors responsible for the tremendous interest foreign insurance companies
are showing in the Indian insurance industry. An insurance survey by LIC and KPMG
revealed that he annual growth in the average insurance premium in India has been 8.2 per
cent compared with the global average of 3-4 per cent. Per capita insurance premium in India
is a mere US $6, one of the lowest in the world. In South Korea, the corresponding figure is
US $ 1,338, in US it is $22,550 and in UK it is $1,589. Insurance premium in India accounts
for a mere 2 per cent of GDP compared to the world average of 7.8 per cent and G-7 average
of 9.2 per cent. Insurance premium as a percentage of savings is barely 5.95 per cent in India
compared to 52.5 per cent in UK. With the entry of private players, the market has been
flooded with new products and customer service has improved. The following table brings
out the low insurance penetration in India as compared to other countries, which is an
indicator of the high potential for growth
There are many researches that present the different dimensions to measure the service
quality across service sectors. To measure service quality and identify the dimensions that
customers consider in evaluating bank services, the most commonly used research instrument
is SERVQUAL (Parasuraman et al., 1988). This SERVQUAL scale for measuring service
quality in a variety of service sectors is used in most studies of bank service quality (Arasli et
al., 2005b; Chi Cui et al., 2003; Lam, 2002; Mels et al., 1997; Othman and Owen, 2001;
Zhou, 2004; Zhou et al., 2002). In addition to the SERVQUAL scale, alternative instruments
are available for specific use in the banking sector (Avkiran, 1994; Bahia and Nantel, 2000;
Aldlaigan and Buttle, 2002; Jabnoun and Al-Tamimi, 2003; Karapte et al., 2005; Guo et al.,
2008), but they have not been used as extensively as SERVQUAL.
2. Literature Review

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Over the past few years, there has been a considerable research on different aspects of service
quality leading to a sound conceptual base for both practioners and researchers. Authors
(Parasuraman et al., 1988; 1991; Carman, 1990) agree that service quality is an abstract
concept, difficult to define and measure. Some of the contemporary definitions of service
quality are summarized in Table 1. On service quality modeling, Gronroos (1984) divides the
customer’s perceptions of any particular service into two dimensions, namely technical and
functional quality. Parasuraman et al. (1985) proposed the gap model of service quality that
operationalised service quality as the gap between expectation and performance perception of
the customer.
Later on, service quality has also been defined broadly as “consumers’ assessment of the
overall excellence or superiority of the service” (Zeithaml et al., 1993). It is viewed as an
attitude or global judgment about the overall excellence of a service, with comparison of
expectations and performance as the measuring tools. Researchers have tried to
operationalised service quality from different perspectives for different service applications.
Based on their conceptual and empirical studies, researchers derived and proposed different
service quality dimensions for various service applications, as illustrated in Table 2.
However, SERVQUAL (Parasuraman et al., 1988; Boulding et al., 1993) and SERVPERF
(Cronin and Taylor, 1992) are the most widely used service quality measurement tools.
SERVQUAL scale measures service quality, based on difference between expectation and
performance perception of customers using 22 items and five-dimensional structure. In the
SERVPERF scale, service quality is operationalised through performance only score based
on the same 22 items and five dimensional structure of SERVQUAL.
The insurance companies offer services that are acceptance products with very few cues to
signal quality. It has been suggested that consumers usually rely on extrinsic cues like brand
image to ascertain and perceive service quality (Gronroos, 1984). This factor is especially
true for a “pure” service such as insurance, which has minor tangible representations of its
quality and is highly relational during most transactions. There is also a lack of price signal in
the market due to specialized customer needs and difficulty in comparing prices; thus
consumers cannot rely solely on price as an extrinsic cue to signal quality.
The life insurance purchase output are often delayed, and thus do not allow immediate post-
purchase valuation. As such, overall satisfaction can’t be immediately measured through an
reaction towards purchase. This situation is more apparent as the future benefits of the
“product” purchased are difficult to foresee and take a long time to “prove” its effects
(Crosby and Stephens, 1987). Infrequent purchase and “usage” of such credence products by
consumers would mean an inability or difficulty in forming service expectations due to
limited understanding of and familiarity with the service (Johnston et al., 1984). At the same
time, because of the amount of money that is typically invested in an insurance policy,
customers seek long-term relationships with their insurance companies and respective agents
in order to reduce risks and uncertainties (Berry, 1995). Pure services like insurance may,
therefore, conjure different expectations than that of services that include tangible products
(Toran, 1993). An insurance policy is almost always sold by an agent who, in 80% of the
cases, is the customer’s only contact (Richard and Allaway, 1993; Clow and Vorhies, 1993;
Crosby and Cowles, 1986). Customers are, therefore, likely to place a high value on their
agent’s integrity and advise
(Zeithaml et al., 1993) The quality of the agent’s service and his/her relationship with the
customer serves to either alleviate or exaggerate the perceived risk in purchasing the life
insurance product. Putting the customer first, and, exhibiting trust and integrity have found to
be essential in selling insurance (Slattery, 1989). Sherden (1987) laments that high quality
service (defined as exceeding “customers’ expectations”) is rare in the life insurance industry
but increasingly demanded by customers. Toran (1993) points out that quality should be at
the core of what the insurance industry does. Customer surveys by Prudential have identified
that customer want more responsive agents with better contact, personalized communications
from the insurer, accurate transactions, and quickly solved problems (Pointek, 1992). A
different study by the National Association of Life Underwriters found other important
factors such as financial stability of the company, reputation of the insurer, agent integrity
and the quality of information and guidance from the agent (King, 1992). Clearly,
understanding consumers’ expectations of life insurance agent’s service is crucial as

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expectations serve as standards or reference points against which service performance is
assessed (Walker and Baker, 2000).Technology has also become an important factor in how
the agent operates in the field including other functions such as distribution, claim costs and
administration (Anonymous, 2004).
Research has shown that the quality of services and the achievement of customer satisfaction
and loyalty are fundamental for the survival of insurers. The quality of after sales services, in
particular, can lead to very positive results through customer loyalty, positive WOM,
repetitive sales and cross-selling (Taylor, 2001).However, many insurers appear unwilling to
take the necessary actions to improve their image. This creates problems for them as the
market is extremely competitive and continuously becomes more so (Taylor, 2001). Previous
studies, notably those of Wells and Stafford (1995), the Quality Insurance Congress (QIC)
and the Risk and Insurance Management Society (RIMS) (Friedman, 2001a, 2001b), and the
Chartered Property Casualty Underwriters (CPCU) longitudinal studies (Cooper and Frank,
2001), have confirmed widespread customer dissatisfaction in the insurance industry,
stemming from poor service design and delivery. Ignorance of customers’ insurance needs
(the inability to match customers perceptions with expectations), and inferior quality of
services largely account for this. The American Customer Satisfaction Index shows that,
between 1994 and 2002, the average customer satisfaction had gone down by 2.5% for life
insurance and 6.1% for personal property insurance respectively (www.theacsi.org). In
Greece, for example, 48% of consumers consider that the industry as a whole is characterized
by lack of professionalism.
It is therefore not surprising that measurement of service quality has generated, and continues
to generate, a lot of interest in the industry (Wells and Stafford, 1995). Several metrics have
been used to gauge service quality. In the United States, for example, the industry and state
regulators have used "complaint ratios" in this respect (www.ins.state.ny.us). The “Quality
Score Card”, developed by QIC and RIMS, has also been used. However, both the complaints
ratios and the quality scorecards have been found to be deficient in measuring service quality
and so a more robust metric is needed. Although service quality structure is found rich in
empirical studies on different service sectors, service quality modeling in life insurance
services is not adequately investigated. Further, for service quality modeling, a set of
dimensions is required, but there seems to be no universal dimension; it needs to be modified
as per the service in consideration. Thus, the dimensions issue of service quality requires
reexamination in context of life insurance services.
There are several studies conducted in a various countries, including: China (Bahia and
Nantel, 2000); the United Arab Emirates (Jabnoun and Al-Tamimi, 2003); China (Lam, 2002;
Guo et al., 2008); South Africa (Mels et al., 1997); Cyprus (Karapte et al., 2005); the UK
(Aldlaigan and Buttle, 2002); Nigeria (Ehigie, 2006); South Korea (Chi Cui et al., 2003);
Kuwait (Othman and Owen, 2001); Australia (Avkiran, 1994; Baumann et al., 2007); and
Malaysia (Amin and Isa, 2008), to name just a few. These studies reflect service quality
assessment on individual countries and further to these studies some more studies have been
done to compare service quality among different countries, (Dash et al., 2009; Glaveli et al.,
2006; Lewis, 1991; Malhotra et al., 2005). Most of these studies are particularly limited
between developed and developing countries. However, cross-cultural service quality studies
have become increasingly relevant as international business flourishes along with a more
integrated global service environment (Arasli et al., 2005a; Dash et al., 2009).
3. Objectives of the Study
Although several researchers have made theoretical and empirical contribution to the study of
service quality in various industries, (like banking, healthcare, education etc) the area of life
insurance is not adequately researched. Some previous studies in this area focused
exclusively on relational qualities (Crosby and Stephens, 1987) and on the generic
SERVQUAL format of quality measurement (Parasuraman et al., 1994).
Following objectives were structured for the purpose of this study:
• To investigate service quality structure for Insurance in India and China.
• To study the level at which services are being well delivered i.e. up-to what level
performances are meeting the expectations.

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• To study the impact of different dimensions on service quality offered in Indian and
Chinese Insurance Companies.
• To assess service quality in the Insurance as perceived by Indian and Chinese service
users.
A review of literature revealed that the earlier studies on measurement of customer perceived
service quality were very few for the life insurance sector world wide. The topic therefore
needs to be investigated.
4. Research Methodology
In order to develop a reliable and valid service quality measurement scale, an empirical study
was undertaken based on methodology .We have used Conclusive Cross-Cultural Descriptive
Research Design to study the service quality structure and its key dimensions in life insurance
sector. The survey instrument was a SERVQUAL type questionnaire relevant to insurance
industry. The questionnaire was divided into two sections. In the first part information related
to different socioeconomic and demographic criteria like income, age, profession, educational
qualification, etc was collected. In the second part, respondents were asked to evaluate
parameters on service quality relevant to insurance industry (on a 5 point scale anchored at
“strongly agree” and “strongly disagree”).
This part consists of 22 statements for both expectations and perception scores, regarding
various aspects of service quality. These service quality aspects were identified by a detailed
exploratory identification process. This included eight focus group discussions (with 40 life
insurance policyholders); eight in-depth interviews (three with branch managers and five with
agents of various life insurance companies).Content analysis of focus group discussions and
depth interviews was performed. In content analysis, the responses (oral as well as written)
were categorized and classified. Then they are coded for tabulation purpose. Thereafter the
frequency counts (of different categories) were compared. These responses were augmented
from current literature in order to draw a wider and more in-depth inventory of service
quality items in life insurance context. Finally, 22 attributes of service quality in life
insurance sector were identified after the process.
4.1.Sample and data collection
Data were gathered through email from customers in China and India. Self-administered
questionnaires were distributed to a convenience sample of customers. Research assistants at
mall entrances asked potential respondents to complete a survey dealing with service quality.
The questionnaire was initially written in English and translated to local languages in
respective countries to post their appropriate responses. In India the survey was conducted in
both English and Hindi and in China most of the customers responded to Chinese language
accurately and positively. Total 176 completed questionnaires were collected in China out of
which 31 were incomplete and eliminated, leaving 145 valid questionnaires for further
analysis. In India, 278 completed questionnaires were collected, out of which 36 were
incomplete which were left from the study making 242 questionnaires for further analysis in
the Indian sample.
Customer Profile
The Customer profile was further tabulated in Table 3. In the Chinese sample, the majority of
respondents were below 40 yrs of age (83%) and ratio of male and female respondents was
61:39 34 percent of Chinese respondents belonged to middle income group. The middle
income group ranged from 1, 00,000-3, 00, 00 Chinese Yuan. In terms of education, 83
percent of the respondents had a university degree, 15 percent had any professional
qualification other than university degree and 16 percent had a secondary school education.
In the Indian sample, a majority of the respondents were male (63 percent). In terms of
income, 53 percent of the respondents were from middle income group which ranges from
4,00,000- 8,00,000 INR. These Chinese and Indian income bands were chosen because they
are broadly comparable in terms of standard of living in the two countries. In terms of
education, 67 percent of the respondents had a university degree, 13 percent had any
professional qualification other than university degree and 19 percent had a secondary school
education.

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4.1.2. Data Analysis
The views of the sample respondents regarding the services offered by the Companies under
study are presented in Table 4. Referring to Table 4; the comparison of expectations and
perceptions of Indian and Chinese Customers, it is observed that the sample customers have
very similar opinion as indicated from the mean values of different dimensions.
The gap (P - E) as shown in Fig. 1 and Fig. 2, is positive for first two factors (i.e. tangibles
and competence) of Indian respondents indicating satisfaction of the customers. In the rest
four factors (i.e. Corporate Image, Technology, personalized financial planning and assurance)
the gap is negative indicating dissatisfaction of the customers, which are also statistically
significant as indicated from the t–values. Further, component wise analysis indicates that the
higher level of dissatisfactions are observed in factors like; i) Adequate numbers of branches;
ii) Simple & Less time consuming Procedure for purchasing a policy, iii) Financially stable
company, iv) Value for money; in all components of Technology, Personalized financial
planning and assurance except Understanding intimately specific needs & Complaint
handling should be prompt, online.
This indicates the major reasons of dissatisfaction of customers in Indian Customers are staff
related.
There are only three components where the customer’s satisfaction is statistically significant
(i.e. accessible location of the branch, Prompt & Efficient Grievance handling mechanism,
prompt and hassle free claims settlement. A comparison between opinion of respondents for
perceptions and expectations exhibits that out of the six dimensions of service quality gaps,
two are positive indicating customers’ satisfaction and rest four are negative indicating
customer dissatisfaction. The levels of satisfaction with Chinese Customers are significant for
Competence dimension, where as they are dissatisfied with assurance dimension (significant
at 5 % level). Further component-wise analysis indicates highest level of satisfaction is
associated with Prompt & Efficient Grievance handling mechanism (0.905) while highest
level of dissatisfaction with Availability of flexible product solution and Trust & Clarity in
explaining policy’s terms and conditions.
The results of SERVQUAL items show similar trend in responses of customers of Indian and
Chinese Companies. The mean scores for both expectation and perception of customers are in
the middle range indicating not very-high levels of expectations from the customers. Figure 1
and 2 present the mean scores of expectations and perceptions of respondents of Indian and
Chinese customers respectively. In exact variations, the quality gap is significant for Chinese
sample but not for the Indian sample is competence (2.011**); while for Indian Customers
but not for Chinese sample is assurance (- 3.099*). Higher differences for mean scores are
observed for Indian Customers, compared to that of Chinese. Principal component analysis
(PCA) was used to interpret the 22 components of service quality for expectations and
perceptions to compare with the initial findings. The findings of the initial models were six
dimensions, as compared with seven dimensions extracted for expectations and perceptions
of the respondents from Chinese Sample. The results of the factor analysis for Chinese
sample are given in Table 6.
For customers’ expectation in Chinese samples, the KMO measures of sampling adequacy is
0.637 and approximate Chi-Square significant at 1 % level, indicating the applicability of
factor analysis.
Similarly, KMO measures 0.698 and significance level of Bartlett’s test of sphericity at 0.000,
suggests the need for factor analysis of performance of Chinese samples as viewed by the
respondents. Total variances explained by the first seven factors are 75.106 %, and 74.321 %
in the analysis of customers’ expectation and perceptions respectively. The solutions for 5 –
components suggested by Zeithmal et al are compared with the sample results indicating
validity of the scales and suggesting the basis in Table 3 for Chinese customers’ expectations
and perception. The KMO measures of sampling adequacy is 0.590 and c2 is significant at
0.000 level indicates the suitability of PCA method for identifying the important components
of expectations of Indian customers. Eight factors have been extracted by the method

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explaining 76.848 percent of the variances in customers’ expectations, taking the cut off point
in the eigen value as ‘1’ (see Table 4). Similarly, the analysis of perception of Indian
respondents suggests five factors extracted through PCA explain 66.582 percent variations
taking the cut off point of eigen value as ‘1’. Further, 1st and 2nd factors combined explain
40.456 % of the variations. Here, the first factor comprised of nine out of the 22 items of
service quality and second factor has clubbed seven items. Again, the content of the five
factors extracted is different from the initial dimensions suggested in the model.
5. Conclusion
These findings emphasize the continuing importance of the employee in providing services
which was supported in research of Dash (2009) for another sector in service industry that
was on Chinese banks . Despite technological automation customers apparently continue to
value person-to-person contact (Molina et al., 2007) that is the reason for negative response
in technological dimensions in both the countries. Despite the changing environment,
customers still assess service quality primarily in terms of the personal support they receive
from employees, rather than technical innovations (Arasli et al., 2005a). According to Molina
et al. (2007), customers expect certain benefits if they are to maintain a long-term relationship
with a particular company. These benefits include first-rate service, personal recognition and
friendly interactions, and a sense of confidence and trust. The findings of the present study,
especially with respect to the Chinese sample of respondents, are in accordance with this
view
Although this study focuses on life insurance industry, however the results can be used for
investigating service quality improvements of life insurance industries of other countries as
well. This can be performed by incorporating necessary changes in service quality aspects in
accordance with socio-economic environment of that nation.
There are, some scope for further research. Future studies in this area should also measure
changes in service quality expectations over time in order to have a better understanding of
how perceptions about service quality relate to satisfaction and loyalty. This is because
service expectations and perceptions are known to be affected by customers’ immediate
reaction to specific service encounters.
The results of this study support the claims of Malhotra et al. (2005) that perceptions of
service quality vary by nationality due to differences in economic, social, and cultural
environments. Researchers are encouraged to replicate this study in different countries.
Considering the debate in the literature about the significance of using country or nationality
as surrogate variables for culture (e.g. Craig and Douglas, 2006), researchers should examine
these differences using a more elaborate conceptualization of culture (e.g. cultural values
orientations). In addition, future research should consider globalization effects (e.g. Craig and
Douglas, 2006) and how they accelerate the emergence of a “global consumer” (e.g.
Cleveland and Laroche, 2007). Previous studies confirm the existence of homogeneous
consumer segments, sharing similar needs and preferences that transcend countries.
References:
Anonymous. (2004). Seizing the initiative. Life Insurance International, April, 11-12.
Asubonteng, P., McCleary, K. J. & Swan, J. E. (1996). SERVQUAL Revisited: A Critical
Review Of Service Quality. Journal of Services Marketing, 10(6), 62-81.
Berry, L. L. (1995). Relationship marketing of services–growing interest, emerging
perspectives. Journal of the Academy of Marketing Science, 23 (Fall), 236-245.
www.ccsenet.org/ibr International Business Research Vol. 3, No. 3; July 2010 Published by
Canadian Center of Science and Education 179
Bitner, M. J., Booms, B. H. & Tetreault, M. S. (1990). The Service Encounter: Diagnosing
Favourable and Unfavourable Incidents. Journal of Marketing, 54(1), 71-84.
Boulding, W., Karla, A., Staelin, R. & Zeithaml, V. A. (1993). A Dynamic Process Model of
Service Quality: From Expectations to Behavioural Intentions. Journal of Marketing
Research, 30(1), 7-27.
Carman, J. M. (1990). Consumer Perceptions of Service Quality: An Assessment of the
SERVQUAL Dimensions. Journal of Retailing, 66 (Spring), 33-55.
Clow, K. F. & Vorhies, D. W. (1993). Building a Competitive Advantage for Service Firms.
Journal of Services Marketing, 7(1), 22-32.

Vol 2, No 5, 2011
8 | P a g e
www.iiste.org
Cooper, R. W. & Frank, G. L. (2001). Key ethical issues facing the property and casualty
insurance: has a decade made a difference? CPCU Journal, 54 (2), 99-111.
Cronin, J. J. Jr. & Taylor, S. A. (1992). Measuring Service Quality: A Reexamination and
Extension. Journal of Marketing, 56 (3), 55-68.
Crosby, L. A. & Cowles, D. (1986). Life Insurance Agents as Financial Planners: A Matter of
Role Consensus. Journal of Professional Services Marketing, 1 (Spring), 69-89.
Crosby, L. A. & Stephens, N. (1987). Effects of relationship marketing on satisfaction,
retention, and prices in the life insurance industry. Journal of Marketing Research,
24(November), 404-411.
Friedman , S. (2001b). RIMS launches quality process. National Underwriter, 105(19), 3-29.
Friedman, S. (2001a). RIMS plans to have third quality scorecard published in 2002.
National Underwriter, 105(18), 3-22.
Gronroos, C. (1984). A service-oriented approach to marketing of services. European
Journal of Marketing, 12 (8), 588-601.
Hampton, G. M. (1993). Gap Analysis of College Student Satisfaction as a Measure of
Professional Service Quality. Journal of Professional Services Marketing, 9(1), 15-28.
Johnson, R. L., Tsiros, M. & Lancioni, R. A. (1995). Masuring Service quality: A Systems
approach. Journal of Services Marketing, 9 (5), 6-19.
Johnston, E. O., O’Connor, R. J. & Zultowski, W. H. (1984). The personal selling process in
the life insurance industry, in J. Jacoby, & C. S. Craig (Eds.), Personal Selling: Theory,
Research and Practice (pp. 136-164). Lexington, MA: Lexington Books.
King, C. (1992). Agents/policy owners split on service. National Underwriter, 41(October), 7.
Lehtinen, U. & Lehtinen, J. R. (1991). Two Approaches to Service Quality Dimensions. The
Service Industries Journal, 11(3), 287-305.
Lewis, B. (1993). Service quality: recent developments in financial services. International
Journal of Bank Marketing, 11(6), 19-25.
Loo, F. (2000). Buying insurance on the net. Financial Planner, February, 58-60.
Marying, P. (2000). Qualitative Content Analysis. Forum: Qualitative Social Research. 1 (2),
Art. 20:June 2000 (www.qualitative-research.net/index.php/fqs/article/.../1089) (Jan 7, 2010).
Mehta, S. C. & Lobo, A. (2002). MSS, MSA and zone of tolerance as measures of service
quality: A Study of the Life Insurance Industry. Second International Services Marketing
Conference, University of Queensland.
Parasuraman, A. & Zeithaml, V. A. & Berry, L. L. (1985). A Conceptual Model of Service
Quality and Its Implications for Future Research. Journal of Marketing, 49(4), 41-50
Parasuraman, A., Berry, L. L. & Zeithaml, V. A. (1991). Refinement and reassessment of the
SERVQUAL scale. Journal of Retailing, 67(4), 420-450.
Parasuraman, A., Zeithaml, V. A. & Berry, L. L. (1988). SERVQUAL: A Multi-Item Scale
for Measuring Consumer Perceptions of Service Quality. Journal of Retailing, 64 (Spring),
21-40.
Parasuraman, A., Zeithaml, V. A. & Berry, L. L. (1994). Alternatives Scales for Measuring
Service Quality: A Comparative Assessment Based on Psychometric and Diagnostic Criteria.
Journal of Retailing, 70(3), 201-230.
Pointek, S. (1992). Outside interests: making the move from lip service to real service.
National Underwriter, 96 (44), 34.
www.ccsenet.org/ibr International Business Research Vol. 3, No. 3; July 2010 180 ISSN
1913-9004 E-ISSN 1913-9012
Rand, G. K. (2004).Diagnosis and Improvement of Service Quality in the Insurance
Industries of Greece and Kenya. Lancaster University Management School Working Paper.
Richard, M. D. & Allaway, A. W. (1993). Service Quality Atrributes and Choice Behaviour.
Journal of Services Marketing, 7(10), 59-68.
Rosen, L. D. & Karwan, K. R. (1994). Prioritizing the Dimensions of Service quality.
International Journal of Service industry Management, 5 (4), 39-52.
Saaty, T. L. (1990). The Analytic Hierarchy Process. Pittsburgh, PA: RWS Publications.
Saaty, T. L. (2001). Decision Making with Dependence and Feedback the Analytic Network
Process, 2nd ed. Pittsburgh, PA: RWS Publications.
Seth, A., Momaya, K. & Gupta, H. M. (2008). Managing the Customer Perceived Service
quality for cellular Mobile Telephony: An Empirical Investigation. Vikalpa, 33 (1), 9-34.

Vol 2, No 5, 2011
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Sherden, W. (1987). The erosion of service quality. Best’s Review, 88 (5), 22.
Siu, N. Y. M. & Cheung, J. T. (2001). A Measure of Retail Service Quality. Marketing
Intelligence and Planning, 19 (2), 88-96.
Slattery, T. (1989). Special report: Nichols: we’ve forgotten the consumer. National
Underwriter, 48 (November), 11.
Stafford, M. R., Stafford, T. F. & Wells, B. P. (1998).Determinants of service quality and
satisfaction in the auto casualty claims process. Journal of Services Marketing, 12, 426-440.
Taylor, S. A. (2001). Assessing the use of regression analysis in examining service recovery
in the insurance industry: relating service quality, customer satisfaction and customer trust.
Journal of Insurance Issues, 24 (1/2), 30-57.
Teas, R. K. (1993). Consumer Expectations and the Measurement of Perceived Service
Quality. Journal of Professional Services Marketing, 8 (2), 33-54.
Toran, D. (1993). Quality service (quality everything!). LIMRA’S Market Facts, 12 (2), 10-11.
Walker, J. & Baker, J. (2000). An exploratory study of a multi-expectation framework for
services. Journal of Services Marketing, 14 (5), 411-431.
Wells, B. P. & Stafford, M. R. (1995). Service quality in the insurance industry: Consumer
perceptions versus regulatory perceptions. Journal of Insurance Regulation, 13, 462-477.
Zeithaml, V. A., Berry, L. L. & Parsuraman, A. (1993). The Nature and Determinants of
Customer Expectations of Service. Journal of the Academy of Marketing Science, 21(1), 1-12.
Table 1
Premium Volume(in
Millions USD)
Change
in %(Nominal)
Change
in %(adjusted
inflation)
Country 2010 2009 2008 2010 2009 2010 2009
China 224919 172425 151473 30.4 13.8 26.2 14.6
India 80521 68528 57434 17.5 19.3 4.9 7.6
Source: Swiss Re.
Table 2 Service quality Dimensions according to usage
Authors Application Areas
Service Quality
Dimensions
Parasuraman, Zeithaml and
Berry
Telephone,brokerage,banks and repair
and maintenance
Reliability
Responsiveness
Assurance
Empathy
Tangibility
Lehtinen
Restaurants,Hotels,Pubs,Food
Junctions
Corporate Quality
Physical Quality
Interactive
Process

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Output
Rosen and Karwan Health care, Teaching
Reliability
Responsiveness
Assurance
Knowing the customers
Tangibility
Access
Siu and Cheung
Retail Stores, Departmental
Stores/Chains
Personal Interaction
Policy
Problem Solving
Physical Appearance
Promises
Problem Solving
Convenience
Mehta and Lobo Life Insurance
Tangibles
Competence
Corporate image
Technology
Personalized financial
planning
Assurance
Table 3 Customer Profile
Parameters
Chinese Indian Total
F % age F %age f %age
Age
Below 30 86 59.31 112 46.28 199 100
30-40 34 23.45 76 31.40 134 100
41-50 19 13.10 34 14.05 68 100
51-60 6 4.14 20 8.26 39 100
Education
upto XIth
24 16.55 46 19.01 66 100
Graduate 64 44.14 98 40.50 208 100
Post Graduate 35 24.14 62 25.62 130 100

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Professional 22 15.17 36 14.88 68 100
Gender
Male 89 61.38 152 62.81 282 100
Female 56 38.62 90 37.19 190 100
Occupation
Salaried 76 52.41 106 43.80 180 100
self employed 36 24.83 83 34.30 133 100
House wife 21 14.48 32 13.22 53 100
Retired 12 8.28 21 8.68 40 100
Income
Higher Income Group 56 38.62 54 22.31 130 100
Middle Income Group 48 33.10 126 52.07 224 100
Lower Income Group 41 28.28 62 25.62 118 100
Table 4 Comparison of Means of Customers Expectation and Performance Indian and Chinese Samples
Component
Indian Chinese
Performance
Expectation
Gap
t-value
Performance
Expectation
Gap
t-value
Tangibles
Adequate No. of branches
5.18
2
5.59
5
-
0.41
3
-
2.447*
*
5.27
4
5.56
8
-
0.29
5
-
1.188
Accessible location of the branch
5.00
8
4.83
1
0.17
7 1.148
4.83
2
4.80
0
0.03
2 0.152
Good ambience of the branch
5.09
5
4.92
6
0.16
9 1.124
4.94
7
4.74
7
0.20
0 0.876
Compete
nce Staff dependable in handling customer’s problems
5.09
5
4.57
0
0.52
5 4.164
4.70
5
4.44
2
0.26
3 1.204

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Efficient Staff
4.98
3
4.73
6
0.24
7 1.729
4.88
4
4.48
4
0.40
0 2.001
Prompt & Efficient Grievance handling
mechanism
5.08
7
4.36
4
0.72
3 4.763*
5.13
7
4.23
2
0.90
5
4.115
*
Prompt and hassle free claims settlement
5.01
7
4.67
8
0.33
9
2.073*
*
4.76
8
4.58
9
0.17
9 0.808
Corporat
e image
Innovativeness in introducing new products
4.84
3
4.61
6
0.22
7 1.482
5.20
0
4.66
3
0.53
7
2.238
**
Simple & Less time consuming Procedure for
purchasing a policy
5.11
6
5.88
4
-
0.76
8
-
5.122*
5.27
4
5.85
3
-
0.57
9
-
2.732
*
Financially stable company
3.48
8
4.00
0
-
0.51
2
-
2.888*
3.51
6
3.76
8
-
0.25
2
-
1.009
Value for money
3.90
1
4.27
3
-
0.37
2
-
2.232*
*
3.81
1
4.07
4
-
0.26
3
-
1.210
Technolo
gy
Easy online transaction
4.17
8
4.83
5
-
0.65
7
-
4.093*
4.31
6
4.73
7
-
0.42
1
-
1.620
Complaint handling should be prompt, online
4.47
5
4.08
7
0.38
8 2.643*
4.73
7
4.28
4
0.45
3
2.151
**
Proactive information through e-mail or SMS
4.18
6
4.86
0
-
0.67
4
-
4.377*
4.57
9
4.73
7
-
0.15
8
-
0.818
Personali
zed
financial
planning
Availability of flexible product solution
4.38
8
5.54
5
-
1.15
7
-
7.708*
4.80
0
5.45
3
-
0.65
3
-
2.922
*
Provisions for Convertibility of products
4.84
7
5.20
2
-
0.35
5
-
2.704*
4.87
4
5.04
2
-
0.16
8
-
0.911
Supplementary services
5.11
6
5.21
1
-
0.09
5 -0.734
4.98
9
5.02
1
-
0.03
2
-
0.179
Provision of Flexible payment schedule
3.98
8
4.10
3
-
0.11
5 -0.675
4.14
7
4.03
2
0.11
5 0.454
Assuranc
e Trained and well-informed agents
4.11
2
4.49
6
-
0.38
-
2.525*
3.86
3
4.50
5
-
0.64
-
2.687

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4 * 2 *
Approaching from customer’s point of view
4.07
0
4.74
4
-
0.67
4
-
4.399*
4.18
9
4.58
9
-
0.40
0
-
1.784
Trust & Clarity in explaining policy’s terms and
conditions
3.87
2
4.68
6
-
0.81
4
-
5.443*
3.86
3
4.49
5
-
0.63
2
-
2.826
*
Understanding intimately specific needs
4.85
1
4.61
6
0.23
5 1.591
4.80
0
4.71
6
0.08
4 0.397
Fig 1. Indian Samples
Fig 2. Chinese Samples
Performance
Expectation
Performance
Expectation

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Table 5 Factor Analysis(Indian)
Expectation
Factors Variables Components Loading Variance explained
Factor-1
Prompt and hassle free claims settlement
Competence/ Corporate
Image/Personalised
Financial
planning/Assurance
0.51
18.33%
Financially stable company 0.689
Value for money 0.631
Provision of Flexible payment schedule 0.863
Trained and well-informed agents 0.804
Approaching from customer’s point of view 0.721
Understanding intimately specific needs 0.621
Factor-2
Competence/ Tangibles/
Corporate
Image/Technology
0.468
15.81%
Staff dependable in handling customer’s
problems
0.766
Efficient Staff 0.846
mechanism
0.681
Innovativeness in introducing new products 0.794
Provisions for Convertibility of products 0.609
Factor-3
Simple & Less time consuming Procedure for
purchasing a policy
Corporate
Image/Technology
0.736
9.69%
Proactive information through e-mail or SMS 0.745
Factor-4
Tangibles
0.856
8.31%
Good ambience of the branch 0.7
Factor-5
Easy online transaction Personalised Financial
planning/Assurance
0.621
8.19%
Availability of flexible product solution 0.738
Factor-6 Complaint handling should be prompt, online Technology 0.808 7.95%
Factor-7
Personalised Financial
planning/Assurance
0.567
6.83%Trust & Clarity in explaining policy’s terms and
conditions
0.755
Perceptions
Factors Variables Components Loading Variance explained
Factor-1
Efficient Staff
Image/Personalised
Financial
planning/Technology
0.737
17.43%
mechanism
0.555
Innovativeness in introducing new products 0.593
Simple & Less time consuming Procedure for 0.585

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purchasing a policy
Proactive information through e-mail or SMS 0.833
Availability of flexible product solution 0.865
Provisions for Convertibility of products 0.718
Factror-2
Corporate Image/
Technology/ Assurance
0.715
16.01%
Easy online transaction 0.673
Complaint handling should be prompt, online 0.522
Approaching from customer’s point of view 0.822
Trust & Clarity in explaining policy’s terms and
conditions
0.766
Factor-3
Tangibles
0.816
12.28%
Accessible location of the branch 0.773
Factor-4
Provision of Flexible payment schedule Personalised Financial
planning/Assurance
0.824
8.24%
Factor-5
Good ambience of the branch
Tangibles/Competence
0.578
7.57%Staff dependable in handling customer’s
problems
0.875
Factor-6
Prompt and hassle free claims settlement Competence/ Corporate
Image
0.774
6.62%
Factor-7
Supplementary services Personalised Financial
planning/Assurance
0.713
6.17%
Understanding intimately specific needs -0.607
Table-6 Factor Analysis(Chinese)
Expectation
Factors Variables Components Loading
Variance
explained
Factor-1
Efficient Staff
Competence/Corporate
Image
0.839
12.74%
Prompt & Efficient Grievance
handling mechanism
0.84
Innovativeness in introducing new
products
0.704
Factor-2
Proactive information through e-
mail or SMS
Technology/
Planning
0.486
12.55%Availability of flexible product
solution
0.913
Provisions for Convertibility of 0.683

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products
Supplementary services 0.74
Factor-3
Provision of Flexible payment
schedule Personalised Financial
Planning/Assurance
0.857
10.07%
Factor -4
Approaching from customer’s point
of view
Assurance
0.757
9.88%
Trust & Clarity in explaining
policy’s terms and conditions
0.844
Understanding intimately specific
needs
0.633
Factor-5
Tangibles/ Competence
0.577
8.86%
Staff dependable in handling
customer’s problems
0.616
Factor-6
Value for money
Corporate
image/Technology
0.589
8.69%
Complaint handling should be
prompt, online
0.737
Factor-7
Image/Tangibles
0.501
7.42%
Prompt and hassle free claims
settlement
0.802
Financially stable company 0.516
Factor-8
Simple & Less time consuming
Procedure for purchasing a policy Corporate image
0.99 6.64%
Perceptions
Factors Variables Components Loading
Variance
explained
Factor-1
Technology/ Corporate
Image/Personalised
Financial
planning/Assurance
0.722
22.08%
Complaint handling should be
prompt, online 0.629
Provision of Flexible payment
schedule 0.622
Approaching from customer’s point
of view 0.825

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Trust & Clarity in explaining
policy’s terms and conditions 0.772
Understanding intimately specific
needs 0.681
Factor-2
Tangibles/Competence/
Corporate Image
0.723
18.38%
Accessible location of the branch 0.734
Staff dependable in handling
customer’s problems 0.742
Efficient Staff 0.609
Innovativeness in introducing new
products 0.573
Simple & Less time consuming
Procedure for purchasing a policy 0.625
Factor-3
Proactive information through e-
mail or SMS
Technology/
planning
0.774
12.10%
Availability of flexible product
solution 0.898
Provisions for Convertibility of
products 0.539
Factor-4
Prompt & Efficient Grievance
handling mechanism
Competence
0.459
7.45%
Prompt and hassle free claims
settlement 0.826
Factor-5
Planning 0.696
6.56%

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